Septa Katmawanti
Public Health Science Study Program, Faculty of Sports Science, Universitas Negeri Malang, Indonesia
Publications
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Research Article
Author(s): Gunawan Widjaja*, Muhammad Nurhisyam Ali Setiawan, Loso Judijanto, Septa Katmawanti, B.M.A.S. Anaconda Bangkara and Endang Fatmawati
This paper examined how data mining may analyse food security data and anticipate community activity constraints. Studies have shown that IRCA measures interrupt agricultural operations, diminish crop yields, risk food shortages, raise food costs, increase food poverty, and deplete nutrients. Data mining can handle huge, complicated information, find hidden patterns and relationships, and anticipate food security outcomes. These enable evidence-based decision-making and proactive actions. However, challenges related to data quality, biases, and reliance on historical data must be addressed. Future directions include integrating real-time data sources, such as satellite imagery and social media data, to capture timely information. Additionally, advanced analytics techniques like deep learning and natural language processing can be utilized to analyze unstructured data. Overcoming chall.. Read More»